三维神经元几何形态生成算法研究进展

doi:10.3969/j.issn.1000-3428.2015.02.031

摘要/Abstract

摘要： 神经元是神经系统的基本构建和计算单元,神经元几何形态的计算模型对理解大脑的结构功能关系及信息处理极其重要。在总结和分析各种三维神经元几何形态生成算法的基础上,给出三维神经元几何形态生成算法的计算框架。根据神经元几何形态生成机制的不同,将生成算法分为基于统计分析的重建算法、基于文法规则的生成算法和基于生物发育的生长算法3 类,并重点比较和分析现有生成算法的优缺点。

关键词: 神经元形态, 虚拟神经元, 数字化重构, 计算模型, 人类脑计划

Abstract: Neurons are the basic building blocks of nervous systems and thus constitute the computational units of the brain. Computational modeling of neuronal morphology is significant for understanding structure-function relationships and brain information processing. This paper introduces the general computational framework of generation algorithms for three-dimensional neuronal morphology,and surveys the advance of the research on generation algorithms,which can be divided into three categories according to the difference of their generation mechanisms:reconstruction algorithms based on statistical analysis, generation algorithms based on grammar rule and growth algorithms based on biological development. By a detailed comparison,the advantages and disadvantages of these algorithms are discussed.

Key words: neuronal morphology, virtual neuron, digital reconstruction, computational model, Human Brain Project (HBP)

中图分类号:

TP301. 6

蔺想红,张玉平,李志强,王佩青. 三维神经元几何形态生成算法研究进展[J]. 计算机工程, doi: 10.3969/j.issn.1000-3428.2015.02.031.

LIN Xianghong,ZHANG Yuping,LI Zhiqiang,WANG Peiqing. Research Progress of Generation Algorithm of 3D Neuronal Morphology[J]. Computer Engineering, doi: 10.3969/j.issn.1000-3428.2015.02.031.

http://www.ecice06.com/CN/Y2015/V41/I2/161

参考文献

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